modelling land use and land cover change with gis and remote sensing

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Modelling land use and land cover change with GIS and remote sensing – what do we miss? Richard Aspinall Macaulay Institute [email protected]

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Page 1: Modelling land use and land cover change with GIS and remote sensing

Modelling land use and land cover change with GIS and remote sensing

– what do we miss?

Richard AspinallMacaulay Institute

[email protected]

Page 2: Modelling land use and land cover change with GIS and remote sensing

Outline

• Importance of land use and land cover change

• Drivers of change• Use of GIS and Remote Sensing

– Examples• What is missing?

– Examples• Conclusion

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 3: Modelling land use and land cover change with GIS and remote sensing

Importance of land change

• 50% of ice-free surface has been transformed by human action

• Since 1850, roughly 35% of anthropogenic CO2 emissions have resulted directly from land use activities

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 4: Modelling land use and land cover change with GIS and remote sensing

Importance of land change

• Human activities now appropriate about 25% of the total global primary production (NPP): 53% by harvest40% by land-use-induced productivity changes7% by human-induced fires

Helmut Haberl, K. Heinz Erb, Fridolin Krausmann, Veronika Gaube, AlberteBondeau, Christoph Plutzar, Simone Gingrich, Wolfgang Lucht,

and Marina Fischer-Kowalski www.pnas.org/cgidoi10.1073/pnas.0704243104

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 5: Modelling land use and land cover change with GIS and remote sensing

Human appropriationof net primary production

Helmut Haberl, K. Heinz Erb, Fridolin Krausmann, Veronika Gaube, AlberteBondeau, Christoph Plutzar, Simone Gingrich, Wolfgang Lucht,

and Marina Fischer-Kowalski www.pnas.org/cgidoi10.1073/pnas.0704243104

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 6: Modelling land use and land cover change with GIS and remote sensing

Agriculture:croplands, pastures and rangelands

• Supports over 6 billion people with food, fibre, etc

• Occupies 40% of global land surface– Cropland: 15.1 million km2

– Pasture: 28.3 million km2 (2000 estimate)• 3.3 billion ruminants graze grasslands

(producing methane)

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 7: Modelling land use and land cover change with GIS and remote sensing

Foley et al Science 2005

Agriculture andFood production

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 8: Modelling land use and land cover change with GIS and remote sensing

Agriculture:Food production

• World grain harvests have doubled in the past four decades to >2 billion tons yr-1

– ~12% increase in (world) cropland area– Green Revolution technologies:

• high-yielding cultivars• chemical fertilizers and pesticides• mechanization and irrigation

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 9: Modelling land use and land cover change with GIS and remote sensing

• During the past 40 years, there has been a~700% increase in global fertilizer use~70% increase in irrigated cropland area

• Agriculture has become the largest source of excess N and P to waterways and coastal zones– surpasses natural ecosystems as principal

source of N emissions– leads to degradation of water quality in many

regions

Agriculture:Consequences of land management change

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 10: Modelling land use and land cover change with GIS and remote sensing

• Urban expansion estimated to consume 1-2 million ha yr-1 of cropland in developing world

• Salinity in irrigated lands is associated with a worldwide loss of ~1.5 million ha yr-1 of arable land (est. $11 billion in production)

• Up to ~40% of global croplands (~ 6 billion ha) may be experiencing some degree of soil erosion, reduced fertility, or overgrazing

Agriculture:land use change

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 11: Modelling land use and land cover change with GIS and remote sensing

Water use

• Global water withdrawals now total ~3900 km3

yr-1, or ~10% of the total global renewable resource

• Consumptive use of water estimated at ~1800 to 2300 km3 yr-1

• Agriculture accounts for nearly 85% of consumptive water use globally

• The extraction of groundwater reserves is almost universally unsustainable and has resulted in declining water tables in many regions

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 12: Modelling land use and land cover change with GIS and remote sensing

How much land?• Currently

– 6 x 109 people– 1.5 x 109 ha of cropland– 2500m2 per person (50x50 m)

• By 2050– 9.2 x 109 people (UN median

projection)– 1.25 x 109 ha (assumes 0.4%

loss p.a.)– 1367m2 per person: 37x37m

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 13: Modelling land use and land cover change with GIS and remote sensing

Outline

• Importance of land use and land cover change

• Drivers of change• Use of GIS and Remote Sensing

– Examples• What is missing?

– Examples• Conclusion

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 14: Modelling land use and land cover change with GIS and remote sensing

Geist, H. J. and Lambin, E. F. (2001) What drives tropical deforestation? A meta-analysis fo proximate and underlying causes of deforestation based on subnational case study evidence. LUCC Report Series no. 4.

Drivers of change…

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 15: Modelling land use and land cover change with GIS and remote sensing

UNDERLYING CAUSES

CONSTRAINTS ON CHOICE

PROXIMATE CAUSES

CONSEQUENCES

Modified from: Geist and Lambin(2002);Birnie et al., (2002)

Land Quality/Suitability

Land Tenure

Social Norms

IndividualPreferences

Finance

Economic

Social

Environmental

External Factors/Trigger Eventse.g. weather, economic shocks

Cultural

Policy and Institutional

Demographic

Economic

Technological

Environmental

Agricultural ChangesCultivation techniquesRanching….

Infrastructure ChangesTransportationMarkets, AgreementsServices

Industrial ChangesEmploymentIndustry…

Drivers of change

Page 16: Modelling land use and land cover change with GIS and remote sensing

Outline

• Importance of land use and land cover change

• Drivers of change• Use of GIS and Remote Sensing

– Examples• What is missing?

– Examples• Conclusion

Page 17: Modelling land use and land cover change with GIS and remote sensing

Snapshots

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 18: Modelling land use and land cover change with GIS and remote sensing

Snapshots

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 19: Modelling land use and land cover change with GIS and remote sensing

Snapshots1946 1988

Land cover change – Cairngorms, Scotland.Source: Land Cover of Scotland 1988 and Land Cover of Scotland ‘Lookback’ studies(Macaulay Institute)

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 20: Modelling land use and land cover change with GIS and remote sensing

Snapshots: Panel analysisThe panel process, conducted at both the pixel and patch

levels: 1. four multispectral satellite images are each categorized

into a thematic LULC classification;2. pattern metrics are run on each of the four LULC

classifications, each producing a set of patch, class, and landscape statistics (here the Interspersion / Juxtaposition Index or IJI and Mean Patch Size or MPS are shown) as well as an output image of the delineated patches;

a. pattern metric output for each of the four times is used to calculate three piecemeal change maps for each pattern metric and each consecutive pair of images (e.g., showing fluctuations in IJI or MPS between two time periods)

b. three pattern change maps are stacked into one panel of all structural change for each given metric (e.g., showing fluctuation in IJI or MPS through all time periods)

3. three thematic change maps are created for each of the time periods represented by the four classifications;

a. the three thematic change maps are stacked to represent the full record of all thematic change across the four classifications

Kelley Crews, University of Texas at Austin

1

2

3

2a

2b3a

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 21: Modelling land use and land cover change with GIS and remote sensing

Stylized trends for land use/land coverchange in Northeast Thailand 1970 to late 1990s

Change in land type Change in pattern metrics

1970 2000 1970 2000

1970 2000Kel

ley

Cre

ws,

Uni

vers

ity o

f Tex

as a

t Aus

tin

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 22: Modelling land use and land cover change with GIS and remote sensing

Outline

• Importance of land use and land cover change

• Drivers of change• Use of GIS and Remote Sensing

– Examples• What is missing?

– Examples • Conclusion

Page 23: Modelling land use and land cover change with GIS and remote sensing

What is missing?

1. What might we miss with snapshots (especially if based on land cover)?

2. What is missing from our understanding of the mechanisms of change (the processes of change behind the drivers)?

3. What aspects of land use and land cover might we investigate further with GIS and Remote Sensing?

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 24: Modelling land use and land cover change with GIS and remote sensing

What is missing?

1. What might we miss with snapshots (especially if based on land cover)?

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 25: Modelling land use and land cover change with GIS and remote sensing

Agricultural Census

• Agricultural (June) census:national, regional andlocal statistics

• Collected since 1866• Data converted to

metric units– Production: metric tons– Yield: metric tons/ha– Area: hectares

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 26: Modelling land use and land cover change with GIS and remote sensing

Areas of major agriculturalland types in Scotland 1900-2006

Are

a (h

a)

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

8,000,000

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Arable Land Rotation Grass Permanent Grass Rough Grazings

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 27: Modelling land use and land cover change with GIS and remote sensing

ARABLE - 1988ARABLE - 1931

Land Cover ofScotland 1988

First Land Utilisation Survey of GB

Hectares4,340,5803,843,385

Arable agriculture: Scotland

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 28: Modelling land use and land cover change with GIS and remote sensing

Areas of major agriculturalland types in Scotland 1900-2006

Are

a (h

a)

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

8,000,000

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Arable Land Rotation Grass Permanent Grass Rough Grazings

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 29: Modelling land use and land cover change with GIS and remote sensing

1922192319241925192619271928192919301931193219331934193519361937

No. of timesyrt <> yrt-1

nmax = 15

4 - 7

8-11

11-15

sprin

g sow

n crop

(barl

ey, o

ats)

autum

n sow

n grai

n (whe

at)

rotati

on gr

ass,

clove

r

root c

rop (tu

rnip,

potat

oes)

perm

anen

t gras

s

1922

1937

The Wicken, Castle Acre,Norfolk

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 30: Modelling land use and land cover change with GIS and remote sensing

L. Dudley Stamp (1948) The Land of Britain, It’s use and misuse. Longmans, Green and Co. Ltd with Geographical Publications Ltd.

After: The Land of Britain: The Report of the Land Utilisation Survey of Britain. Part 70, Report on Norfolk by Mosby, J. E. G. (1938)

Crop rotation

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 31: Modelling land use and land cover change with GIS and remote sensing

The Wicken, Castle AcreNorfolk

2007

Source: GoogleEarth

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 32: Modelling land use and land cover change with GIS and remote sensing

Snaphots to model change

Need to consider spatial units (eg farm, parcel – not pixel)

192219231924192519261927 1928 1929 1930

1931 1932 1933 1934

1935 1936 1937

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 33: Modelling land use and land cover change with GIS and remote sensing

Major land uses and animal numbers in Scotland

Are

a (h

a)

0

4,000,000

8,000,000

12,000,000

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

8,000,000

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Arable Land Rotation Grass Permanent Grass Rough Grazings

Cattle

Sheep

coun

t

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 34: Modelling land use and land cover change with GIS and remote sensing

What is missing?

1. What might we miss with snapshots (especially if based on land cover)?

2. What is missing from our understanding of the mechanisms of change (the processes of change behind the drivers)?

• Technological• Structural (policy)• Cultural/Social• Economic

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 35: Modelling land use and land cover change with GIS and remote sensing

1. Technological change

• Crop breeding and yield/production• Mechanisation of agriculture

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 36: Modelling land use and land cover change with GIS and remote sensing

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 20100

2

4

6

8 Barley

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010012456 Oats

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 201002468

10 Wheat

t/ha

t/ha

t/ha

Crop breeding:increased yield

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 37: Modelling land use and land cover change with GIS and remote sensing

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 20100

50,000

100,000

150,000

200,000

250,000Horses for Agricultural Use

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010Year

0

20000

40000

60000

80000Combines + Tractors

Mechanisation of agriculture

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 38: Modelling land use and land cover change with GIS and remote sensing

Technological change

• Technological innovation• Diffusion and adoption of technology

• Not a change in use or cover, but has considerable importance (for natural and human systems)

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 39: Modelling land use and land cover change with GIS and remote sensing

1800 1810 1820 1830 1840 1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010Year

0

200,000

400,000

600,000

800,000

1,000,000Oats.tonnes

1800 1810 1820 1830 1840 1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 20100

50,000

100,000

150,000

200,000

250,000

Horses for Agricultural Use

Associated consequences

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 40: Modelling land use and land cover change with GIS and remote sensing

2. Structural (Policy) change

• Common Agricultural Policy – price support– overproduction in 1980s– Set aside (EU) – 1988 onwards– LFA Payments– High Nature Value areas– CAP Reform– …

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 41: Modelling land use and land cover change with GIS and remote sensing

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 20100

40000

80000

120000

160000

Whe

at.h

a

Area sown toWheat, Scotland

Common Agricultural Policy:Price Support

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 42: Modelling land use and land cover change with GIS and remote sensing

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010Year

0

30000

60000

90000

120000

Seta

side

+ B

areF

allo

w.h

a Bare Fallow + Set aside, Scotland

Common Agricultural Policy:Set aside

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 43: Modelling land use and land cover change with GIS and remote sensing

Structural (Policy) change

• Policy creation: decision-making• Adoption: decision-making

(even, in some places, where this required a massive change in farming practice, for example from grazing to arable)

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 44: Modelling land use and land cover change with GIS and remote sensing

3. Cultural/Social change

• amenity and lifestyles– Rocky Mountains in the US have seen

explosive growth in number of people and in housing

– Change linked to lifestyle and amenity preferences

–(demographic and cultural change)

Example: Gallatin County, Montana, USA

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 45: Modelling land use and land cover change with GIS and remote sensing

Gallatin County: New HomesGallatin County Population 1890-2000

14079 15864 16124 18269 21902 2604532505

42865

6246 9553

50463

67831

020000400006000080000

Trouper Trail from Triple Tree Ranch Subdivision

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 46: Modelling land use and land cover change with GIS and remote sensing

Properties

Pre-1890

Early Settlement

1890-1934

Rapid Settlement

1935-1966

Adjustment

1967-1984

Resource reallocation

1985-2000

Resource reallocation

well and septic permit records (1860-2000)- Locations of properties

- Date

Site: WaterWoodlandSlope

Amenity: Proximity to National ForestView from property - Visibility

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 47: Modelling land use and land cover change with GIS and remote sensing

Proximity to National Forest Visibility

Amenity

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 48: Modelling land use and land cover change with GIS and remote sensing

Models for different times

Model Pre-1890 1890-1934 1935-1966 1967-1984 1985-2000

Variables

Period

BozemanSlopeWaterForest

RailroadSlopeWaterForest

TownsSlopeWaterForest

BozemanSlopeNat Forest

BozemanSlopeNat ForestVisibility

Pre-1890 0.521 0.126 0.098 0.184 0.071

1890-1934 0.000 1.000 0.000 0.000 0.000

1935-1966 1.000 0.000 0.000 0.000 0.000

1967-1984 0.000 0.000 0.000 0.691 0.309

1985-2000 0.000 0.000 0.000 0.331 0.668

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 49: Modelling land use and land cover change with GIS and remote sensing

Gallatin County, Montana

• Amenity is a relatively recent influence on change

• Processes: reflects choices and decisions based on values, attitudes, and beliefs as well as economics and finance

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 50: Modelling land use and land cover change with GIS and remote sensing

4. Economic change• Globalization• World markets• Change in relative price and demand for fuel and food• …

US Maize production for ethanol:2006-7: 2 billion bushels out of 12 million bushels (16.6%)2007-8: forecast to rise to 3.5 billion bushels (35%)

70 new ethanol plants are under construction – this will double the amount of maize consumed for fuel (Autumn 2007 data)

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 51: Modelling land use and land cover change with GIS and remote sensing

Processes producing change

• Technological change– Innovation, diffusion

• Structural, Cultural, Economic– Decision-making, regulation

• Decisions and choices– Based on knowledge, values, attitudes,

beliefs, preferences, …

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 52: Modelling land use and land cover change with GIS and remote sensing

Decision making

www.globallandproject.org

Land-coverBiophysical control

Land-useHuman control

EcologicalSystems

BiogeochemistryBiodiversity

WaterAir, Soil

SocialSystemsPopulation

Social/Economic structurePolitical/institution regime

Culture, Technology

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 53: Modelling land use and land cover change with GIS and remote sensing

What is missing?

1. What might we miss with snapshots (especially if based on land cover)?

2. What is missing from our understanding of the mechanisms of change (the processes of change behind the drivers)?

3. What aspects of land use and land cover might we investigate further (with GIS and Remote Sensing)?

Page 54: Modelling land use and land cover change with GIS and remote sensing

Animalsand animal husbandry

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 55: Modelling land use and land cover change with GIS and remote sensing

Animal husbandry

0

4,000,000

8,000,000

12,000,000

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Cattle

Sheep

coun

t

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 56: Modelling land use and land cover change with GIS and remote sensing

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010Year

0

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000Sheep

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 20100

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

Cattle

Animal numbers

Cattle

Sheep

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 57: Modelling land use and land cover change with GIS and remote sensing

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010Year

0

200,000

400,000

600,000

800,000

1,000,000Pigs

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 20100

5,000,000

10,000,000

15,000,000

20,000,000

Poultry

Poultry

Pigs

Animal numbers

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 58: Modelling land use and land cover change with GIS and remote sensing

Nitrogen:Cattle, horse, sheep manure, inorganic fertilizer

1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990Year

0

50000000

100000000

150000000

200000000

250000000

300000000

N (k

g)

Inorganic fertilizer – barley, oats, wheat

Cattle, horse, sheep manure

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 59: Modelling land use and land cover change with GIS and remote sensing

Major land uses and animal numbers in Scotland

Are

a (h

a)

0

4,000,000

8,000,000

12,000,000

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

8,000,000

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Arable Land Rotation Grass Permanent Grass Rough Grazings

Cattle

Sheep

coun

t

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 60: Modelling land use and land cover change with GIS and remote sensing

Land management

Changes in, and types of, land management are important, especially in relation to land function (e.g. provision of ecosystem services)

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 61: Modelling land use and land cover change with GIS and remote sensing

Land management

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions

Page 62: Modelling land use and land cover change with GIS and remote sensing

Conclusions

1. Influence of processes, rather than drivers, of change

• Decisions2. Land (use) systems:

e.g. agriculture• Animal Systems and Husbandry• Land Management practices

3. Land ‘functions’ – how land systems work, what they do: ecological (environmental) goods and services

Outline Land managementImportance Drivers of change GIS use What is missing? Drivers Animals Conclusions